1. Field of the Invention
The present invention relates generally to the field of computer-implemented inventions, and more specifically, to a system and method for cross-selling products and services across an enterprise.
2. Description of the Related Art
Virtually every company in the world involved in selling products or services to its consumer base is interested in strengthening its relationship with those consumers. The ability to increase the number and type of products and/or services sold to each consumer, while ensuring that the sale of those products and services benefits both the consumer and the company, is key to these relationships. Cross-selling products and services to customers, however, poses certain technological challenges.
By way of example, companies in the financial services industry are customarily organized into separate business silos or lines of business (LOBs), each of which is responsible for its own performance and contribution to the profitability of the enterprise as a whole. These separate LOBs often view their current and prospective consumers as prospects only for their own particular product lines because the idea of cross-selling products from another LOB is perceived as a threat to—or at least competitive with—the sale of their own products. Given limited opportunities in which to capture a consumer's interest, each LOB assumes that any opportunity must be used to sell its products, even if selling a different product would benefit both the consumer and the enterprise more. With this individualized focus, cooperative cross-sell strategies are time-consuming, expensive and difficult to implement, resulting in missed enterprise-level opportunities to sell products and services from multiple LOBs. The complex tasks of analyzing and fine-tuning cross-sell strategies for high sales volume while accurately tracking and managing risk exposure is further complicated by the lack of integration between LOBs.
Because each LOB is responsible for its specific goals, each LOB must have decision-making autonomy. Unfortunately, the technology solutions currently available to assist with automated decision-making at the LOB level discourage or prevent centralized control in areas where such control is beneficial to the enterprise. With each LOB implementing its own controls to ensure compliance with regulatory requirements such as the Fair Credit Reporting Act (FCRA), the Fair and Accurate Credit Transactions Act (FACT), and the Gramm-Leach-Bliley Act (GLBA), enterprise-level investment in these controls is unnecessarily high, and the risk of inconsistent and erroneous implementation of such controls is greatly increased.
Given the heavy merger and acquisition activity in the financial services sector, many companies have experienced a proliferation in automated point of contact (POC) systems, each with its own technology platform and most of which do not communicate with one another. As one institution merges with or acquires another, the automated POC systems of each institution are often left in place, making it extremely difficult to implement a technology platform that integrates those functions and is deployed in a more centralized fashion. The various LOBs generate sales leads, manage consumer information, and process applications in one or more of their own separate systems, perpetuating the problem related to offering their current and prospective consumers a consistent experience.
With multiple systems responsible for various pieces of the institution's view of its consumer, it is extremely difficult to get a complete picture from any one system. For example, a branch teller using a financial transaction POC system to help a consumer deposit his paycheck into his checking account may have no idea that the consumer has an available Home Equity Line of Credit (HELOC) offer that was generated when a branch customer service representative helped the consumer open his checking account earlier in the month on a different POC system. Even if the consumer's initial reaction to the offer was positive, the opportunity for the teller to reinforce the offer and close the sale is lost, simply because system A did not know what had taken place in system B. It is no wonder the consumer often comes away with the impression that the financial institution does not value or even recognize her needs.
The separate technology platforms used by multiple POC systems has resulted in each LOB being responsible for acquiring its own credit bureau and other external data used in determining risk and other aspects of its consumers' pertinent spending behavior and needs. This situation has led to redundant and unnecessarily expensive integration with the various data providers and has hindered or prevented sharing of such data between LOBs.
Improvements in technology have enabled consumer contact through a growing number of distribution channels. Consumers can conduct their business and shop for products and services via traditional brick and mortar branches, home loan offices, telephone call centers, loan and insurance brokerage offices, automated teller machines (ATMs), and Internet sites, to name a few. With little or no integration between these various contact points, the consumer is presented with an inconsistent and often confusing experience. In most cases, no attempt is made to understand the consumer's needs beyond the immediate purpose of the current contact, and a significant opportunity to strengthen the consumer relationship is lost.
In today's marketplace, financial institutions are extremely dynamic in their business practices. In addition to expansion through mergers and acquisitions, they constantly add and remove product lines to meet the needs of their consumers. It is not uncommon for new product lines to be accompanied by new technology platforms intended to reach the consumer either through an existing or a new distribution channel. These new technology platforms add to the integration challenge, and while they may address a new consumer need, they make understanding the complete picture of the consumer all the more difficult. With data about their existing consumers spread among multiple systems, financial institutions lack the ability to use all of that data in a comprehensive fashion.
The notion of the uncaring, remote, mega financial service provider has led to a recent revival in growth of the small, high-touch financial service company. Smaller companies are often on a first name basis with their consumers but are unable to manage and analyze their risk and cross-sell strategies simply because they cannot accumulate the data needed to do so.
Traditional direct mail campaigns have targeted millions of households with solicitations to apply for various products and services, most notably in the credit card arena. Credit card offers, for example, arrive by mail on such a frequent basis that most consumers simply throw away the offer without ever looking at it. These campaigns are costly in terms of compiling the solicitation lists, mailing the solicitation and processing the responses. Historically, although expensive and time-consuming to implement, these campaigns have less than a one percent success rate where the targeted consumer actually accepts the solicitation.
In contrast with mass direct mail campaigns, acceptance rates for offers presented at the time the consumer has initiated contact with a financial institution have proven to be far higher, often by an order of magnitude. When a consumer initiates contact with a financial institution, she is often more receptive to offers that pertain to her specific needs. For example, being able to identify additional products the consumer may need at the time she is opening up a new checking account represents a far better opportunity to make the sale than if an offer for additional products was delivered in the mail. When identifying these potential offers involves analyzing the consumer's credit report data, the process is commonly referred to as “instant prescreen” processing.
The ability to perform live instant prescreen processing for additional products is not something a financial institution can perform on its own behalf due to regulations defined in the FCRA. These regulations prohibit lenders from having direct access to a consumer's credit report file unless the consumer has explicitly requested a credit product and given her permission (explicit or implicit) for the lender to obtain her credit report data. Instead, the institutions have been forced to use one or more of the credit reporting agencies to perform the credit data analysis on a large population of consumers and then resort to costly mail campaigns with limited effectiveness. In addition to regulatory concerns, the technical challenges of integrating one, let alone multiple, POC systems with the each of the various credit bureaus and other data providers needed to enable instant prescreen processing are daunting.
While large institutions are able to offer more robust product lines and leverage economies of scale to compete on price and features, they lack the ability to provide outstanding consumer service because of their inability to capture integrated, comprehensive views of their consumers' needs and current situations. The smaller company can offer outstanding consumer service, but it cannot compete with larger institutions in terms of product features and price because of the traditionally high cost of acquiring new and retaining existing consumers. Furthermore, the available consumer base is rapidly becoming saturated with redundant products and services offered by many of the providers seeking consumers' business. The ability to differentiate offers on price and feature, with the focus on efficiently meeting specific consumer needs, is an objective widely sought by small financial institutions.
As competition increases for consumer loyalty and the right to provide the products and services the consumer is interested in owning, the consumer's ability to shop for products and services and take her business elsewhere has also increased. The key to existing consumer retention and new consumer acquisition is the ability to analyze the effectiveness of cross-sell and credit risk strategies and to quickly and safely implement changes to those strategies. With the proliferation of POC systems and distribution channels, along with individualized LOB focus, financial institutions do not have a consolidated source of data to perform such analysis. They are forced to cobble together information from multiple sources and in varying technical formats, limiting their ability to quickly analyze data and respond to their consumers' needs.
The ability to handle increased consumer interest generated by a highly successful marketing campaign is another challenge facing financial institutions. Often referred to as scalability, the goal is to provide cost-effective means of handling normal, everyday activity while being able to process spikes in activity. For example, consider the impact of a Super Bowl advertisement for a new home equity loan product. The last thing a lender wants is to be forced to turn consumers away because its automated solutions are not up to the task of handling a sharp increase in activity.
With the advent of the Internet and other new technologies, consumers are able to get instant answers to questions, purchase products and services, research and compare products all in far less time than ever before. This age of instant gratification affects the way financial institutions must respond to their consumers' needs. Traditional loan application processes involving a paper application being submitted and followed by a several-day period where the lender evaluates the application and makes a decision of whether or not to grant credit to the consumer are no longer sufficient. Consumers expect and demand a much faster turnaround process, and lenders who can respond with an instant, real-time decision are far more likely to retain existing and acquire new consumers.
There is no automated solution on the market today that addresses all of these issues. A successful solution must ensure enterprise-level consistency, compliance and control while enabling LOB-level autonomy for managing cross-sell strategies, credit decisioning and risk-based pricing. A successful solution must also provide easily deployed integration options for dealing with multiple POC systems with consumer contact being made via any available channel. Access to all available product line offers no matter what POC system or distribution channel is being utilized by the consumer, together with the ability to perform instant prescreen processing and traditional consumer-initiated credit decisioning with access to any credit bureau or other external data source are all important aspects required of any complete solution.
In addition, the solution must be provided in an environment that ensures high availability and scalability along with strict security and regulatory compliance. In the current marketplace, consumers are able to conduct their financial business and obtain new products and services 24 hours a day, 7 days a week, and they demand 100% protection of their personal and financial data while doing it. Financial institutions that experience even a minor breach in security that allows consumer information to fail into the hands of someone intending to commit fraud are subject to significant punitive penalties and potentially unrecoverable damage to their reputation in the marketplace.
These same institutions are saddled with multiple delivery channels and POC systems and have traditionally been forced to invest large amounts of capital, energy, and human resources in meeting these needs. An integrated solution, with security and compliance controls implemented in one place, as opposed to separately for each LOB and POC system, is what is needed. If an integrated solution can be accessed in an application service provider (ASP) environment, the financial institution stands to gain even more in terms of cost-effectiveness and consistency in meeting security and regulatory compliance.